This AREA project will extend a model of neuromuscular planning from two- to three-dimensional workspaces. The posture-based model of motor planning (Rosenbaum, Meulenbroek, Vaughan, & Jansen, in press, Psychological Review) simulates how people perform such actions as reaching, grasping, reaching around obstacles, hitting, or tapping, when they must select a particular goal posture, and trajectory to it, from among the infinite number of possibilities. The model is based on the retrieval of stored postures (instance retrieval) and the synthesis of novel postures (instance generation) in order to perform tasks defined by sets of constraints (such as accuracy, obstacle avoidance, and efficiency). The first step is to extend the algorithms now used in the model to three-dimensional workspaces, by developing algorithms for search in posture space, smooth interpolation between postures, and the detection of obstacles that may lie in movement paths. The second step is to construct workspaces, both tangible and virtual, in which a number of specific predictions of the model may be tested, including the effects of experience on performance, and the model's predictions of how compensation for injury or other restriction of movement at a particular joint may be achieved. The AREA project will add to the opportunities for intensive research participation by Hamilton undergraduates, by supporting three undergraduates each summer and by providing an intensified research experience during the academic year.